Important new developments have appeared since the most recent direct survey on shape
correspondence published almost a decade ago. Our survey covers the period from 2011 …

Recent advancements in self-driving cars, robotics, and remote sensing have widened the
range of applications for 3D Point Cloud (PC) data. This data format poses several new …

Shape completion, the problem of estimating the complete geometry of objects from partial
observations, lies at the core of many vision and robotics applications. In this work, we …

Template 3D shapes are useful for many tasks in graphics and vision, including fitting
observation data, analyzing shape collections, and transferring shape attributes. Because of …

The ability to generate novel, diverse, and realistic 3D shapes along with associated part
semantics and structure is central to many applications requiring high-quality 3D assets or …

In this paper, we study the problem of semantic annotation on 3D models that are
represented as shape graphs. A functional view is taken to represent localized information …

We introduce a novel neural network architecture for encoding and synthesis of 3D shapes,
particularly their structures. Our key insight is that 3D shapes are effectively characterized by …

This paper introduces a deep architecture for segmenting 3D objects into their labeled
semantic parts. Our architecture combines image-based Fully Convolutional Networks …

We introduce SDM-NET, a deep generative neural network which produces structured
deformable meshes. Specifically, the network is trained to generate a spatial arrangement of …

Problems such as equipment defects or limited viewpoints will lead the captured point
clouds to be incomplete. Therefore, recovering the complete point clouds from the partial …